>won't the time taken to make scientific discoveries - or really discoveries of any kind - begin to tend to zero?

No.

Many discoveries are only enabled by somebody being in the right place at the right time to make an important observation, or somebody creatively getting interested in a question nobody else thought to ask. These serendipitous moments happen unpredictably. Many questions can't be answered without extensive data collection specifically to answer them, and that consumes time or in-person resources an AI might not have at its disposal, unless we want it to blanket the planet in drones it can use to study everything at once.

For example, I study salmon populations. Many of the questions we ask rely on knowing how many salmon of a particular kind came back from the ocean each year. We basically get one data point per year, and we can't say much from one data point. If we're carefully monitoring a population, which is expensive and time-consuming, it still takes decades to build up a dataset with a large enough sample size to draw useful conclusions. There is no way to speed that up.

Likewise, much of basic research in medical science involves testing things in other organisms, from cell lines to nematodes to fruit flies to mice. Many testing methods rely on random chance, with biologists breeding tons of these critters until a particular genetic variant they want arises, and they can then use it to test some hypothesis. The time to run experiments is generally based on the life cycles of the study organisms, which aren't instantaneous.

Also, there is no chance that "everything is discovered," ever, because there are constantly new things to discover. There are new things happening that we want to understand. In my field, there might be a worrisome fluctuation in a salmon population one year, and the only way to find its cause is to go out and collect some time-consuming data. It can't be deduced from first principles or past data because something new and unusual is happening. New and unusual things are happening everywhere, all the time.

I expect AGI/ASI to be a transformative partner for scientists, capable of both facilitating and making great discoveries. But some of the predictions for ASI are just over-the-top and don't reflect how knowledge is really gained. No amount of digital genius can produce data that haven't been collected yet, nor draw correct conclusions from inadequate sample sizes, nor collect independent samples faster than the study subjects generate them.

Also, regarding the positive feedback loop of AI development and exponential growth / recursive self-improvement, know that pretty much nothing grows exponentially forever. The faster it grows, the faster it reaches asymptotes where progress is limited by something different from whatever was limiting it before.